{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Use below for charts in dark jupyter theme\n",
    "params = {\"ytick.color\" : \"w\",\n",
    "          \"xtick.color\" : \"w\",\n",
    "          \"axes.labelcolor\" : \"w\",\n",
    "          \"axes.edgecolor\" : \"w\"} \n",
    "plt.rcParams.update(params)\n",
    "\n",
    "import xai\n",
    "import xai.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_path = 'data/adult.data'\n",
    "categorical_cols = [\"gender\", \"workclass\", \"education\", \"education-num\", \"marital-status\",\n",
    "                   \"occupation\", \"relationship\", \"ethnicity\", \"native-country\", \"loan\"]\n",
    "csv_columns = [\"age\", \"workclass\", \"fnlwgt\", \"education\", \"education-num\", \"marital-status\",\n",
    "                   \"occupation\", \"relationship\", \"ethnicity\", \"gender\", \"capital-gain\", \"capital-loss\",\n",
    "                   \"hours-per-week\", \"native-country\", \"loan\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>education-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>gender</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "      <th>loan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass   education  education-num       marital-status  \\\n",
       "0   39          State-gov   Bachelors             13        Never-married   \n",
       "1   50   Self-emp-not-inc   Bachelors             13   Married-civ-spouse   \n",
       "2   38            Private     HS-grad              9             Divorced   \n",
       "3   53            Private        11th              7   Married-civ-spouse   \n",
       "4   28            Private   Bachelors             13   Married-civ-spouse   \n",
       "\n",
       "           occupation    relationship ethnicity   gender  capital-gain  \\\n",
       "0        Adm-clerical   Not-in-family     White     Male          2174   \n",
       "1     Exec-managerial         Husband     White     Male             0   \n",
       "2   Handlers-cleaners   Not-in-family     White     Male             0   \n",
       "3   Handlers-cleaners         Husband     Black     Male             0   \n",
       "4      Prof-specialty            Wife     Black   Female             0   \n",
       "\n",
       "   capital-loss  hours-per-week    loan  \n",
       "0             0              40   <=50K  \n",
       "1             0              13   <=50K  \n",
       "2             0              40   <=50K  \n",
       "3             0              40   <=50K  \n",
       "4             0              40   <=50K  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = xai.data.load_census()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(csv_path, names=csv_columns)\n",
    "del df[\"fnlwgt\"]\n",
    "del df[\"native-country\"]\n",
    "df.head()\n",
    "df.to_csv(\"../xai/data/census.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "target = \"loan\"\n",
    "protected = [\"ethnicity\", \"gender\", \"age\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ims = xai.show_imbalances(df, protected)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "im = xai.show_imbalance(df, \"gender\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bal_df = xai.balance(df, \"gender\", upsample=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "im = xai.show_imbalance(bal_df, \"gender\", cross=[\"loan\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bal_df = xai.balance(df, \"gender\", cross=[\"loan\"], upsample=1)\n",
    "im = xai.show_imbalance(bal_df, \"gender\", cross=[\"loan\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1200, 12)\n"
     ]
    }
   ],
   "source": [
    "\n",
    "proc_df = xai.normalize_numeric(bal_df)\n",
    "proc_df = xai.convert_categories(proc_df)\n",
    "x = proc_df.drop(\"loan\", axis=1)\n",
    "y = proc_df[\"loan\"]\n",
    "\n",
    "x_train, y_train, x_test, y_test = xai.balanced_train_test_split(\n",
    "            x, y, cross=[\"gender\"], \n",
    "            categorical_cols=categorical_cols, min_per_class=300,\n",
    "            fallback_type=\"half\")\n",
    "\n",
    "print(x_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_test = x_test.copy()\n",
    "df_test[\"loan\"] = y_test\n",
    "\n",
    "_= xai.show_imbalance(df_test, \"gender\", cross=[\"loan\"], categorical_cols=categorical_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import sklearn\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, mean_squared_error, roc_curve, auc\n",
    "\n",
    "from keras.layers import Input, Dense, Flatten, \\\n",
    "    Concatenate, concatenate, Dropout, Lambda\n",
    "from keras.models import Model, Sequential\n",
    "from keras.layers.embeddings import Embedding\n",
    "\n",
    "def build_model(X):\n",
    "    input_els = []\n",
    "    encoded_els = []\n",
    "    dtypes = list(zip(X.dtypes.index, map(str, X.dtypes)))\n",
    "    for k,dtype in dtypes:\n",
    "        input_els.append(Input(shape=(1,)))\n",
    "        if dtype == \"int8\":\n",
    "            e = Flatten()(Embedding(X[k].max()+1, 1)(input_els[-1]))\n",
    "        else:\n",
    "            e = input_els[-1]\n",
    "        encoded_els.append(e)\n",
    "    encoded_els = concatenate(encoded_els)\n",
    "\n",
    "    layer1 = Dropout(0.5)(Dense(100, activation=\"relu\")(encoded_els))\n",
    "    out = Dense(1, activation='sigmoid')(layer1)\n",
    "\n",
    "    # train model\n",
    "    model = Model(inputs=input_els, outputs=[out])\n",
    "    model.compile(optimizer=\"adam\", loss='binary_crossentropy', metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "\n",
    "def f_in(X, m=None):\n",
    "    \"\"\"Preprocess input so it can be provided to a function\"\"\"\n",
    "    if m:\n",
    "        return [X.iloc[:m,i] for i in range(X.shape[1])]\n",
    "    else:\n",
    "        return [X.iloc[:,i] for i in range(X.shape[1])]\n",
    "\n",
    "def f_out(probs, threshold=0.5):\n",
    "    \"\"\"Convert probabilities into classes\"\"\"\n",
    "    return list((probs >= threshold).astype(int).T[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "59312/59312 [==============================] - 1s 10us/step - loss: 0.5508 - acc: 0.7170\n",
      "Epoch 2/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.4199 - acc: 0.8065\n",
      "Epoch 3/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3813 - acc: 0.8251\n",
      "Epoch 4/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3714 - acc: 0.8280\n",
      "Epoch 5/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3673 - acc: 0.8311\n",
      "Epoch 6/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3662 - acc: 0.8318\n",
      "Epoch 7/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3640 - acc: 0.8338\n",
      "Epoch 8/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3626 - acc: 0.8343\n",
      "Epoch 9/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3630 - acc: 0.8335\n",
      "Epoch 10/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3619 - acc: 0.8356\n",
      "Epoch 11/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3605 - acc: 0.8360\n",
      "Epoch 12/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3605 - acc: 0.8359\n",
      "Epoch 13/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3601 - acc: 0.8377\n",
      "Epoch 14/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3590 - acc: 0.8360\n",
      "Epoch 15/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3593 - acc: 0.8364\n",
      "Epoch 16/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3589 - acc: 0.8363\n",
      "Epoch 17/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3589 - acc: 0.8373\n",
      "Epoch 18/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3586 - acc: 0.8365\n",
      "Epoch 19/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3590 - acc: 0.8364\n",
      "Epoch 20/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3586 - acc: 0.8364\n",
      "Epoch 21/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3582 - acc: 0.8367\n",
      "Epoch 22/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3581 - acc: 0.8370\n",
      "Epoch 23/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3573 - acc: 0.8378\n",
      "Epoch 24/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3575 - acc: 0.8372\n",
      "Epoch 25/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3576 - acc: 0.8366\n",
      "Epoch 26/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3574 - acc: 0.8370\n",
      "Epoch 27/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3574 - acc: 0.8376\n",
      "Epoch 28/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3570 - acc: 0.8375\n",
      "Epoch 29/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3570 - acc: 0.8368\n",
      "Epoch 30/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3573 - acc: 0.8377\n",
      "Epoch 31/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3567 - acc: 0.8371\n",
      "Epoch 32/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3567 - acc: 0.8368\n",
      "Epoch 33/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3571 - acc: 0.8377\n",
      "Epoch 34/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3567 - acc: 0.8386\n",
      "Epoch 35/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3566 - acc: 0.8371\n",
      "Epoch 36/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3558 - acc: 0.8375\n",
      "Epoch 37/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3561 - acc: 0.8376\n",
      "Epoch 38/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3565 - acc: 0.8372\n",
      "Epoch 39/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3558 - acc: 0.8376\n",
      "Epoch 40/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3558 - acc: 0.8374\n",
      "Epoch 41/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3555 - acc: 0.8378\n",
      "Epoch 42/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3555 - acc: 0.8389\n",
      "Epoch 43/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3558 - acc: 0.8378\n",
      "Epoch 44/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3562 - acc: 0.8371\n",
      "Epoch 45/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3547 - acc: 0.8378\n",
      "Epoch 46/50\n",
      "59312/59312 [==============================] - 0s 3us/step - loss: 0.3548 - acc: 0.8381\n",
      "Epoch 47/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3553 - acc: 0.8366\n",
      "Epoch 48/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3550 - acc: 0.8383\n",
      "Epoch 49/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3542 - acc: 0.8383\n",
      "Epoch 50/50\n",
      "59312/59312 [==============================] - 0s 4us/step - loss: 0.3545 - acc: 0.8384\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcb03c264e0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model(proc_df.drop(\"loan\", axis=1))\n",
    "\n",
    "model.fit(f_in(x_train), y_train, epochs=50, batch_size=512)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1200/1200 [==============================] - 0s 53us/step\n",
      "Error 0.3332: \n",
      "Accuracy 83.6667: \n"
     ]
    }
   ],
   "source": [
    "score = model.evaluate(f_in(x_test), y_test, verbose=1)\n",
    "print(\"Error %.4f: \" % score[0])\n",
    "print(\"Accuracy %.4f: \" % (score[1]*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "probabilities = model.predict(f_in(x_test))\n",
    "pred = f_out(probabilities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_= xai.metrics_imbalance(\n",
    "        x_test, \n",
    "        y_test, \n",
    "        probabilities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alejandro/anaconda3/lib/python3.6/site-packages/xai-0.0.3-py3.6.egg/xai/__init__.py:520: RuntimeWarning: invalid value encountered in long_scalars\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_= xai.metrics_imbalances(\n",
    "        x_test, \n",
    "        y_test, \n",
    "        probabilities,\n",
    "        columns=protected,\n",
    "        categorical_cols=categorical_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_= xai.roc_imbalance(\n",
    "    x_test, \n",
    "    y_test, \n",
    "    probabilities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_= xai.roc_imbalances(\n",
    "    x_test, \n",
    "    y_test, \n",
    "    probabilities, \n",
    "    columns=protected,\n",
    "    categorical_cols=categorical_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_= xai.pr_imbalances(\n",
    "    x_test, \n",
    "    y_test, \n",
    "    probabilities, \n",
    "    columns=protected,\n",
    "    categorical_cols=categorical_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alejandro/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:189: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = xai.smile_imbalance(\n",
    "    y_test, \n",
    "    probabilities)\n",
    "\n",
    "# d.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alejandro/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:189: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = xai.smile_imbalance(\n",
    "    y_test, \n",
    "    probabilities,\n",
    "    display_breakdown=True)\n",
    "# d.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alejandro/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:189: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = xai.smile_imbalance(\n",
    "    y_test, \n",
    "    probabilities,\n",
    "    bins=9,\n",
    "    threshold=0.75,\n",
    "    manual_review=0.375,\n",
    "    display_breakdown=False)\n",
    "# d.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "age\n",
      "workclass\n",
      "education\n",
      "education-num\n",
      "marital-status\n",
      "occupation\n",
      "relationship\n",
      "ethnicity\n",
      "gender\n",
      "capital-gain\n",
      "capital-loss\n",
      "hours-per-week\n"
     ]
    }
   ],
   "source": [
    "for c in x.columns: \n",
    "    print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>education-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>gender</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.028167</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>-0.00125</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.092333</td>\n",
       "      <td>0.0175</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.002083</td>\n",
       "      <td>0.005917</td>\n",
       "      <td>0.044917</td>\n",
       "      <td>0.006917</td>\n",
       "      <td>0.01225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        age  workclass  education  education-num  marital-status  occupation  \\\n",
       "0  0.028167    -0.0015   -0.00125          0.037        0.092333      0.0175   \n",
       "\n",
       "   relationship  ethnicity    gender  capital-gain  capital-loss  \\\n",
       "0       0.01975   0.002083  0.005917      0.044917      0.006917   \n",
       "\n",
       "   hours-per-week  \n",
       "0         0.01225  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_avg(x, y):\n",
    "    return model.evaluate(f_in(x), y, verbose=0)[1]\n",
    "\n",
    "imp = xai.feature_importance(x_test, y_test, get_avg)\n",
    "\n",
    "imp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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